There are also works considering implicit bias of other first-order optimization algorithms. [1]} worked on Stochastic Gradient Descent for linear logistic regression. [2]} studied the implicit bias of mirror descent, natural gradient descent, and steepest descent on linear model. [3]} proved gradient descent on Neural Tangent Kernel will converge linearly to a global minimum near the initial point.
